Search results for: Learning vector quantization neural network
4005 Traffic Forecasting for Open Radio Access Networks Virtualized Network Functions in 5G Networks
Authors: Khalid Ali, Manar Jammal
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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.
Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5564004 Impacts of E-learning in Nursing Education: In the Light of Recent Studies
Authors: A.Ö. İlkay, C.O. Zeynep
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Information and Communication Technologies (ICT) has changed our life and learn. ICT bares doors to new innovative methods to deliver education. E-learning is a part of ICT and has been endorsed as a tool for developing “21st century skills” in higher education. The aim of this review is to establish the impacts of e-learning in undergraduate nursing education. A systematic literature review was conducted to assess the impacts of e-learning in nursing education by using Akdeniz University electronic databases. According to results, we can decelerate that the nursing faculties cannot treat e-learning methods as a single tool. E-learning should be used with a good understanding of learners’ needs.
Keywords: E-learning, nursing education, systematic literature review.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46454003 Students’ Perceptions of Mobile Learning: Case Study of Kuwait
Authors: Rana AlHajri, Salah Al-Sharhan, Ahmed Al-Hunaiyyan
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Mobile learning is a new learning landscape that offers opportunity for collaborative, personal, informal, and students’ centered learning environment. In implementing any learning system such as a mobile learning environment, learners’ expectations should be taken into consideration. However, there is a lack of studies on this aspect, particularly in the context of Kuwait higher education (HE) institutions. This study focused on how students perceive the use of mobile devices in learning. Although m-learning is considered as an effective educational tool in developed countries, it is not yet fully utilized in Kuwait. The study reports on the results of a survey conducted on 623 HE students in Kuwait to a better understand students' perceptions and opinions about the effectiveness of using mobile learning systems. An analysis of quantitative survey data is presented. The findings indicated that Kuwait HE students are very familiar with mobile devices and its applications. The results also reveal that students have positive perceptions of m-learning, and believe that video-based social media applications enhance the teaching and learning process.
Keywords: Higher education, mobile learning, social media, students’ perceptions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34384002 Matching-Based Cercospora Leaf Spot Detection in Sugar Beet
Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu
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In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.
Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22014001 Retaining Users in a Commercially-Supported Social Network
Authors: Sasiphan Nitayaprapha
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A commercially-supported social network has become an emerging channel for an organization to communicate with and provide services to customers. The success of the commercially-supported social network depends on the ability of the organization to keep the customers in participating in the network. Drawing from the theories of information adoption, information systems continuance, and web usability, the author develops a model to explore how a commercially-supported social network can encourage customers to continue participating and using the information in the network. The theoretical model will be proved through an online survey of customers using the commercially-supported social networking sites of several high technology companies operating in the same sector. The result will be compared with previous studies to learn about the explanatory power of the research model, and to identify the main factors determining users’ intention to continue using a commercially-supported social network. Theoretical and practical implications and limitations are discussed.
Keywords: Social network, Information adoption, Information systems continuance, Web usability, User satisfaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19014000 Learning Difficulties of Children with Disabilities
Authors: Chalise Kiran
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The learning difficulties of children with disabilities are always a matter of concern when we talk about educational needs and quality education of children with disabilities. This paper is the outcome of the review of the literature focused on the educational needs and learning difficulties of children with disabilities. For the paper, different studies written on children with disabilities and their education were collected through search engines. The literature put together were analyzed from the angle of learning difficulties faced by children with disabilities and the same were used as a precursor to arrive at the findings on the learning of the children. The analysis showed that children with disabilities face learning difficulties. The reasons for these difficulties could be attributed to factors in terms of authority, structure, school environment and behaviors of teachers and parents and the society as a whole.
Keywords: Children with disabilities, learning difficulties, education of children with disabilities, disabled children.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4313999 Virtualization Technology as a Tool for Teaching Computer Networks
Authors: Dalibor Dobrilovic, Borislav Odadžic
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In this paper is being described a possible use of virtualization technology in teaching computer networks. The virtualization can be used as a suitable tool for creating virtual network laboratories, supplementing the real laboratories and network simulation software in teaching networking concepts. It will be given a short description of characteristic projects in the area of virtualization technology usage in network simulation, network experiments and engineering education. A method for implementing laboratory has also been explained, together with possible laboratory usage and design of laboratory exercises. At the end, the laboratory test results of virtual laboratory are presented as well.Keywords: Computer network simulation software, teaching networking concepts, virtual network laboratory, virtualization technology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22943998 Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption
Authors: Kenichiro Hida, Shin-Ichi Kuribayashi
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In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.
Keywords: Virtual routing function, NFV, resource allocation, minimum power consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13173997 Bi-Criteria Latency Optimization of Intra-and Inter-Autonomous System Traffic Engineering
Authors: K. Vidya, V.Rhymend Uthariaraj
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Traffic Engineering (TE) is the process of controlling how traffic flows through a network in order to facilitate efficient and reliable network operations while simultaneously optimizing network resource utilization and traffic performance. TE improves the management of data traffic within a network and provides the better utilization of network resources. Many research works considers intra and inter Traffic Engineering separately. But in reality one influences the other. Hence the effective network performances of both inter and intra Autonomous Systems (AS) are not optimized properly. To achieve a better Joint Optimization of both Intra and Inter AS TE, we propose a joint Optimization technique by considering intra-AS features during inter – AS TE and vice versa. This work considers the important criterion say latency within an AS and between ASes. and proposes a Bi-Criteria Latency optimization model. Hence an overall network performance can be improved by considering this jointoptimization technique in terms of Latency.Keywords: Inter-Domain Routing , Measurement, OptimizationPerformance, Traffic Engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15213996 An Extension of Multi-Layer Perceptron Based on Layer-Topology
Authors: Jānis Zuters
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There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capability in certain cases. The new model requires additional computational resources to compare to the classic model, nevertheless the loss in efficiency isn-t regarded to be significant.
Keywords: Learning algorithm, multi-layer perceptron, topology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15183995 Knowledge Mining in Web-based Learning Environments
Authors: Nittaya Kerdprasop, Kittisak Kerdprasop
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The state of the art in instructional design for computer-assisted learning has been strongly influenced by advances in information technology, Internet and Web-based systems. The emphasis of educational systems has shifted from training to learning. The course delivered has also been changed from large inflexible content to sequential small chunks of learning objects. The concepts of learning objects together with the advanced technologies of Web and communications support the reusability, interoperability, and accessibility design criteria currently exploited by most learning systems. These concepts enable just-in-time learning. We propose to extend theses design criteria further to include the learnability concept that will help adapting content to the needs of learners. The learnability concept offers a better personalization leading to the creation and delivery of course content more appropriate to performance and interest of each learner. In this paper we present a new framework of learning environments containing knowledge discovery as a tool to automatically learn patterns of learning behavior from learners' profiles and history.Keywords: Knowledge mining, Web-based learning, Learning environments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17923994 Neural Networks Approaches for Computing the Forward Kinematics of a Redundant Parallel Manipulator
Authors: H. Sadjadian , H.D. Taghirad Member, A. Fatehi
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In this paper, different approaches to solve the forward kinematics of a three DOF actuator redundant hydraulic parallel manipulator are presented. On the contrary to series manipulators, the forward kinematic map of parallel manipulators involves highly coupled nonlinear equations, which are almost impossible to solve analytically. The proposed methods are using neural networks identification with different structures to solve the problem. The accuracy of the results of each method is analyzed in detail and the advantages and the disadvantages of them in computing the forward kinematic map of the given mechanism is discussed in detail. It is concluded that ANFIS presents the best performance compared to MLP, RBF and PNN networks in this particular application.Keywords: Forward Kinematics, Neural Networks, Numerical Solution, Parallel Manipulators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19363993 A Novel Adaptive E-Learning Model Based on Developed Learner's Styles
Authors: Hazem M. El-Bakry, Ahmed A. Saleh, Taghreed T. Asfour
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Adaptive e-learning today gives the student a central role in his own learning process. It allows learners to try things out, participate in courses like never before, and get more out of learning than before. In this paper, an adaptive e-learning model for logic design, simplification of Boolean functions and related fields is presented. Such model presents suitable courses for each student in a dynamic and adaptive manner using existing database and workflow technologies. The main objective of this research work is to provide an adaptive e-learning model based learners' personality using explicit and implicit feedback. To recognize the learner-s, we develop dimensions to decide each individual learning style in order to accommodate different abilities of the users and to develop vital skills. Thus, the proposed model becomes more powerful, user friendly and easy to use and interpret. Finally, it suggests a learning strategy and appropriate electronic media that match the learner-s preference.Keywords: Adaptive learning, Learning styles, Teaching strategies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20293992 A Study on Early Prediction of Fault Proneness in Software Modules using Genetic Algorithm
Authors: Parvinder S. Sandhu, Sunil Khullar, Satpreet Singh, Simranjit K. Bains, Manpreet Kaur, Gurvinder Singh
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Fault-proneness of a software module is the probability that the module contains faults. To predict faultproneness of modules different techniques have been proposed which includes statistical methods, machine learning techniques, neural network techniques and clustering techniques. The aim of proposed study is to explore whether metrics available in the early lifecycle (i.e. requirement metrics), metrics available in the late lifecycle (i.e. code metrics) and metrics available in the early lifecycle (i.e. requirement metrics) combined with metrics available in the late lifecycle (i.e. code metrics) can be used to identify fault prone modules using Genetic Algorithm technique. This approach has been tested with real time defect C Programming language datasets of NASA software projects. The results show that the fusion of requirement and code metric is the best prediction model for detecting the faults as compared with commonly used code based model.Keywords: Genetic Algorithm, Fault Proneness, Software Faultand Software Quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19913991 A Comparative Study of Novel Opportunistic Routing Protocols in Mobile Ad Hoc Networks
Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya
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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data packets and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.
Keywords: Expected Transmission Count (ETX), Opportunistic routing, Proactive Source Routing (PSR), throughput.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24153990 Echo State Networks for Arabic Phoneme Recognition
Authors: Nadia Hmad, Tony Allen
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This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia dialectic and 34 speakers from the Center for Spoken Language Understanding (CSLU2002) database of speakers with different dialectics from 12 Arabic countries. Results for the KAPD and CSLU2002 Arabic databases show phoneme recognition performances of 72.31% and 38.20% respectively.
Keywords: Arabic phonemes recognition, echo state networks (ESNs), neural networks (NNs), supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24133989 Comparative Analysis of Machine Learning Tools: A Review
Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha
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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18623988 Meta Model Based EA for Complex Optimization
Authors: Maumita Bhattacharya
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Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiencyKeywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20723987 Anomaly Detection using Neuro Fuzzy system
Authors: Fatemeh Amiri, Caro Lucas, Nasser Yazdani
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As the network based technologies become omnipresent, demands to secure networks/systems against threat increase. One of the effective ways to achieve higher security is through the use of intrusion detection systems (IDS), which are a software tool to detect anomalous in the computer or network. In this paper, an IDS has been developed using an improved machine learning based algorithm, Locally Linear Neuro Fuzzy Model (LLNF) for classification whereas this model is originally used for system identification. A key technical challenge in IDS and LLNF learning is the curse of high dimensionality. Therefore a feature selection phase is proposed which is applicable to any IDS. While investigating the use of three feature selection algorithms, in this model, it is shown that adding feature selection phase reduces computational complexity of our model. Feature selection algorithms require the use of a feature goodness measure. The use of both a linear and a non-linear measure - linear correlation coefficient and mutual information- is investigated respectivelyKeywords: anomaly Detection, feature selection, Locally Linear Neuro Fuzzy (LLNF), Mutual Information (MI), liner correlation coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21953986 Specialized Reduced Models of Dynamic Flows in 2-Stroke Engines
Authors: S. Cagin, X. Fischer, E. Delacourt, N. Bourabaa, C. Morin, D. Coutellier, B. Carré, S. Loumé
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The complexity of scavenging by ports and its impact on engine efficiency create the need to understand and to model it as realistically as possible. However, there are few empirical scavenging models and these are highly specialized. In a design optimization process, they appear very restricted and their field of use is limited. This paper presents a comparison of two methods to establish and reduce a model of the scavenging process in 2-stroke diesel engines. To solve the lack of scavenging models, a CFD model has been developed and is used as the referent case. However, its large size requires a reduction. Two techniques have been tested depending on their fields of application: The NTF method and neural networks. They both appear highly appropriate drastically reducing the model’s size (over 90% reduction) with a low relative error rate (under 10%). Furthermore, each method produces a reduced model which can be used in distinct specialized fields of application: the distribution of a quantity (mass fraction for example) in the cylinder at each time step (pseudo-dynamic model) or the qualification of scavenging at the end of the process (pseudo-static model).
Keywords: Diesel engine, Design optimization, Model reduction, Neural network, NTF algorithm, Scavenging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13363985 A General Model for Amino Acid Interaction Networks
Authors: Omar Gaci, Stefan Balev
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In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we identify a number of properties of these networks. We compare them to the general small-world network model and we analyze their hierarchical structure.Keywords: interaction network, protein structure, small-world network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15863984 Japanese Language Learning Strategies Based on Gender by Japanese Learners in North Sulawesi Indonesia
Authors: Sherly Ferro Lensun
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Strategies influence the language abilities of both male and female learners in the learning process. Therefore, learning strategies are one of the critical factors for improving language learning and are essential as part of the initial learning effort. In general, language learning strategies differ between boys and girls. Therefore, this research aims to obtain a model that investigates the relationship between the selection of learning strategies, their frequency of use, and the learner's gender. In addition, we found differences in strategy use and their impact on language ability between males and females. 137 students participated and completed the questionnaire. There were 48 males (35%) and 90 females (65.7%). It was clear that most of the Japanese learners were women. Findings show that most Japanese learners in North Sulawesi used cognitive and social strategies and methods of involving others in learning Japanese.
Keywords: Learning strategies, Japanese Language, Gender by Japanese Learners, North sulawesi.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2413983 A Study and Implementation of On-line Learning Diagnosis and Inquiry System
Authors: YuLung Wu
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In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.Keywords: Knowledge Structure Graph, On-line LearningDiagnosis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14713982 Fuzzy Logic Speed Control of Three Phase Induction Motor Drive
Authors: P.Tripura, Y.Srinivasa Kishore Babu
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This paper presents an intelligent speed control system based on fuzzy logic for a voltage source PWM inverter-fed indirect vector controlled induction motor drive. Traditional indirect vector control system of induction motor introduces conventional PI regulator in outer speed loop; it is proved that the low precision of the speed regulator debases the performance of the whole system. To overcome this problem, replacement of PI controller by an intelligent controller based on fuzzy set theory is proposed. The performance of the intelligent controller has been investigated through digital simulation using MATLAB-SIMULINK package for different operating conditions such as sudden change in reference speed and load torque. The simulation results demonstrate that the performance of the proposed controller is better than that of the conventional PI controller.Keywords: Fuzzy Logic, Intelligent controllers, Conventional PI controller, Induction motor drives, indirect vector control, Speed control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 65083981 Offline Handwritten Signature Recognition
Authors: Gulzar A. Khuwaja, Mohammad S. Laghari
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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capability to reliably distinguish between an authorized person and an imposter. Signature verification systems can be categorized as offline (static) and online (dynamic). This paper presents a neural network based recognition of offline handwritten signatures system that is trained with low-resolution scanned signature images.Keywords: Pattern Recognition, Computer Vision, AdaptiveClassification, Handwritten Signature Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29093980 Automatically Driven Vector for Guidewire Segmentation in 2D and Biplane Fluoroscopy
Authors: Simon Lessard, Pascal Bigras, Caroline Lau, Daniel Roy, Gilles Soulez, Jacques A. de Guise
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The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.
Keywords: Edge detection, Line Enhancement, Segmentation, Fluoroscopy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17323979 An Enhanced AODV Routing Protocol for Wireless Sensor and Actuator Networks
Authors: Apidet Booranawong, Wiklom Teerapabkajorndet
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An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.
Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22573978 DTC-SVM Scheme for Induction Motors Fedwith a Three-level Inverter
Authors: Ehsan Hassankhan, Davood A. Khaburi
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Direct Torque Control is a control technique in AC drive systems to obtain high performance torque control. The conventional DTC drive contains a pair of hysteresis comparators. DTC drives utilizing hysteresis comparators suffer from high torque ripple and variable switching frequency. The most common solution to those problems is to use the space vector depends on the reference torque and flux. In this Paper The space vector modulation technique (SVPWM) is applied to 2 level inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the torque ripple. Then the controller based on space vector modulation is designed to be applied in the control of Induction Motor (IM) with a three-level Inverter. This type of Inverter has several advantages over the standard two-level VSI, such as a greater number of levels in the output voltage waveforms, Lower dV/dt, less harmonic distortion in voltage and current waveforms and lower switching frequencies. This paper proposes a general SVPWM algorithm for three-level based on standard two-level SVPWM. The proposed scheme is described clearly and simulation results are reported to demonstrate its effectiveness. The entire control scheme is implemented with Matlab/Simulink.Keywords: Direct torque control, space vector Pulsewidthmodulation(SVPWM), neutral point clamped(NPC), two-levelinverter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 44013977 Analysis of Education Faculty Students’ Attitudes towards E-Learning According to Different Variables
Authors: Eyup Yurt, Ahmet Kurnaz, Ismail Sahin
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The purpose of the study is to investigate the education faculty students’ attitudes towards e-learning according to different variables. In current study, the data were collected from 393 students of an education faculty in Turkey. In this study, theattitude towards e‐learning scale and the demographic information form were used to collect data. The collected data were analyzed by t-test, ANOVA and Pearson correlation coefficient. It was found that there is a significant difference in students’ tendency towards e-learning and avoidance from e-learning based on gender. Male students have more positive attitudes towards e-learning than female students. Also, the students who used the internet lesshave higher levels of avoidance from e-learning. Additionally, it is found that there is a positive and significant relationship between the number of personal mobile learning devices and tendency towards e-learning. On the other hand, there is a negative and significant relationship between the number of personal mobile learning devices and avoidance from e-learning. Also, suggestions were presented according to findings.
Keywords: Education faculty students, attitude towards e-learning, gender, daily Internet usage time, m-learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21673976 Comparison of Performance between Different SVM Kernels for the Identification of Adult Video
Authors: Hajar Bouirouga, Sanaa El Fkihi , Abdeilah Jilbab, Driss Aboutajdine
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In this paper we propose a method for recognition of adult video based on support vector machine (SVM). Different kernel features are proposed to classify adult videos. SVM has an advantage that it is insensitive to the relative number of training example in positive (adult video) and negative (non adult video) classes. This advantage is illustrated by comparing performance between different SVM kernels for the identification of adult video.Keywords: Skin detection, Support vector machine, Pornographic videos, Feature extraction, Video filtering, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2313